Large Power Transformers Research Articles

Thermal Analysis of Power Transformer Using 2D and 3D Finite Element Method

An accurate simulation and computational analysis of temperature distribution in large power transformers used in power plants is crucial during both the design and operational phases. This study introduces a thermal modeling analysis encompassing two- and three-dimensional (2D and 3D) approaches for power transformers. The mathematical model for heat diffusion follows the Finite Element Method (FEM) approach. Validation of the computed results involves comparing them against measurements from Hyundai’s test report for both 2D and 3D models, aiming to identify the most effective solution. Additionally, the thermal dynamics of power transformers under diverse operational conditions, specifically oil-immersed ones, are examined. The efficacy of this model is confirmed through testing on a step-up transformer at Kureimat station in Egypt, with specifications including three-phase, 50 Hz, 16.5/240 KV, nine taps, and cooling type (ONAN/ONAF1/ONAF2).

Adsorption sensitivity and sensing performance of Au-doped Ti3C2O2 gas sensor for fault characteristic gases in power transformer

By analyzing the compositions and concentration of dissolved gases in power transformer oil, it is possible to effectively identify and predict the types and degrees of internal faults in oil-immersed transformers. This technology is currently an important method for fault diagnosis and prevention of large oil-immersed power transformers. This study established two different adsorption systems, namely Ti3C2O2 and Ti3C2O2 doped with Au atom, for the detection of four fault characteristic gases (CO, CO2, C2H4, CH4) in power transformer oil. The research results indicate that Ti3C2O2 exhibits inadequate adsorption capabilities for the above gases. The maximum adsorption energy is only −0.440 eV, which belongs to physical adsorption. After doping with Au atoms, the adsorption sensitivity of Ti3C2O2 for the above gases was significantly improved, with a significant increase in adsorption energy and charge transfer. The average adsorption energy has increased by 435%, and the minimum adsorption energy is also −0.660 eV. The adsorption process changed from physical adsorption to chemical adsorption. These research results provide a theoretical basis for Au-doped Ti3C2O2 gas sensor in detecting fault characteristic gases in power transformer.

Investigating Aging Characteristics of Oil-Immersed Power Transformers' Insulation in Electrical-Thermal-Mechanical Combined Conditions.

The condition and health of large oil-immersed power transformers' insulation have a direct impact on the safety and stability of the power grid. Therefore, it is crucial to investigate the aging characteristics of oil-paper insulation in power transformers. In this study, we developed a computational model for reclosing current calculation and multiphysics coupling models for magnetic-circuit-force, electrostatic field, and temperature field simulations. The calculated aging resulted in a mechanical stress of 8.71 MPa, an electric field strength of 2.26 × 106 V/m, and a temperature of 113.7 °C. We conducted combined electrical-thermal-mechanical aging tests on the oil-paper insulation and measured various insulating paper performance parameters at different aging stages. Our study revealed that both the mechanical and electrical properties of the insulating paper deteriorated in both aging groups. However, the changes were more pronounced in the electrical-thermal-mechanical aging group compared to the electrical-thermal aging group, indicating that mechanical stress accelerated the aging process of the insulating paper. In the early stages of aging, the rate of performance changes in the electrical-thermal aging group was similar to that in the electrical-thermal-mechanical aging group. However, as the aging time increased, the degradation of performance induced by mechanical aging became more significant. This suggests that the insulating paper's resistance to mechanical damage, specifically short-circuit resistance, noticeably decreased after prolonged aging.

Simulation Study on the Motion Characteristics and Influencing Factors of Fiber Impurity Particles in Oil Flow in a Typical Distributed Electric Field

There have been many studies on the motion and aggregation characteristics of fiber impurities in insulation oil under static conditions. However, there are few studies on the motion characteristics of fiber impurities in insulation oil under flow conditions. In large power transformers, insulation oil is constantly in a state of flow. As a result, the motion characteristics of fiber impurities suspended in the insulation oil are even more complex due to the effects of oil flow. This study constructed a multi-physics field model for single-particle fibrous impurities in solid-liquid two-phase flow and systematically analyzed its motion characteristics. The study shows that the collision frequency between fiber impurity particles and electrodes with the same effective area is negatively correlated with the degree of electric field distortion. The maximum particle velocity and collision frequency of fibrous impurities in both uniform and slightly non-uniform electric fields show an almost linear relationship with the particle size radius. Additionally, the slope of the relationship decreases gradually with an increase in oil flow rate. With the increase of particle size, under the same flow velocity, an increase in the maximum velocity of the fibrous particles and the number of collisions with the electrodes. thereby increasing the probability of fibrous impurities transferring charge between the electrodes. Compared to the motion characteristics of fibrous impurity particles under static conditions, oil flow mainly affects the collision frequency between fibrous impurity particles and electrodes, reducing the probability of particle transfer.

Modeling magnetostriction of grain-oriented sheet steels based on magnetization process and domain motion

Grain-oriented (GO) sheet steels are preferred for magnetic cores in large power transformers because of their low core loss and high permeability. However, GO sheet steels exhibit more complex magnetostriction than non-oriented (NO) materials, causing undesirable vibrations and acoustic noises in the transformer core, especially under certain operating conditions, such as DC bias and magnetic saturation. This paper proposes a magnetostriction model of GO sheet steels based on an improved understanding of the magnetization process and domain motion. Incorporating the positive and negative magnetostriction components attributed to domain wall motion and rotation, the proposed model can accurately reproduce the butterfly loops in a wide range of magnetization along the rolling direction (RD) of GO material. Its effectiveness and accuracy are verified by the experimental measurements.

Analysis of Bubble Motion Characteristics in Oil Based on Level Set Method

At present, transformer oil is the primary insulation method for large power transformers, and the dynamic behavior of bubbles in transformer oil can impact the insulation performance of transformer oil. Therefore, based on the level set method in this paper, the motion characteristics of bubbles in two structures, a horizontal oil channel and a vertical oil channel, under various conditions of different bubble numbers, different flow velocities, and different bubble sizes are studied using finite element simulation. The simulation results show that the kinetic behavior of bubbles becomes more complicated as the radius increases, the number of bubbles increases, and the flow velocity increases. At the same time, the bubble expansion and deformation is a cyclic process due to the electric field force, laminar flow and surface tension in the bubble suspension process.

Monitoring Transformer Condition with MLP Machine Learning Model

Failures of large power transformers in transmission system are always followed by significant costs, which is especially problematic because they present an unplanned expenditure. Aside from derailing financial plans, these events can lead to lower system reliability. This paper describes the development and potential application of transformer model based on multilayer perceptron class of artificial neural networks. Model is built in Python programming language and data collected over the span of one year for a single transformer. Three input features (oil temperature, winding current and outside temperature) are used in the input layer, with the goal of predicting the winding temperature in the transformer. Predicted temperature of the windings can then be compared with the actual winding temperature, which can serve as an indicator of transformers internal condition. Two types of transformer condition degradation are simulated to show the model in action, and certain indicators are explored.

Studying Intelligent Techniques Acting in Large Power Transformer Monitoring

Studying Intelligent Techniques Acting in Large Power Transformer Monitoring

A Reliability Improvement Technology of Transformer Internal Inspection Robot and Its Control System

The oil-immersed transformer internal inspection robot has played a good role in the inspection of large power transformers, effectively reducing the working intensity of staff and improving the automation level of power equipment inspection. However, in practical work, this kind of internal inspection robot often has various quality problems and a high failure rate. Aiming at the various complex environmental stresses faced by the internal detection robot, this paper analyzes the performance failure mechanism and completes the research on the reliability improvement method of the internal inspection robot and its control system, which effectively improves the reliability of the internal inspection manipulator.

Application of Polymer Matrix Composites in Large Power Transformer Tanks

Large Power Transformers (LPT) are a major element of the modern transmission grid. The tanks of traditional LPTs are made of low carbon steel which could contribute to their overall weight. This study provides a preliminary evaluation and selection process to modernize LPT tank materials following well-established principles of advanced materials engineering. A primary objective of this study was to select an advanced material for an LPT tank to make it more resilient to potential in-service structural damage. The selection process resulted in five advanced composite materials based on glass and carbon fibers with epoxy and phenolic resins employing two different fiber architectures. These composites were further screened to identify the most suitable materials considering several environmental conditions that the tank could be exposed to in service. As part of the final materials selection analysis, the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method was employed for the final ranking of the LPT tank replacement materials. Preliminary recommendations of modifications to the composites to withstand the effects of the thermal, electrical, and electromagnetic environment of the LPT are presented.

Dynamic Thermal Model for Oil Directed Air Forced Power Transformers With Cooling Stage Representation

Power transformers are critical assets for generation and grid. Controlling their aging is an essential task to ensure the availability of installations, and to optimize maintenance and operational costs over their lifetime. Large power transformers do not always operate at their full cooling capacity, and the cooling efficiency is often adjusted by steps (each different step being also called a “cooling stage”) based on the top-oil, winding temperature indicator or hot-spot temperature. Various dynamic thermal models exist in the literature, but none of them provide easy-to-use correction factors to consider the effect of the cooling stage on the coolers’ thermal resistance as well as on top-oil and hot-spot gradients. The purpose of this article is to propose a simple yet accurate model for the thermal monitoring of Oil Directed Air Forced power transformers. Several applications of the model are given such as cooling efficiency monitoring, evaluation of the load capability (or loadability), and coolers temperature control improvement.

Voiceprint Feature Extraction of Large Power Transformers in Uninterrupted Diagnosis and Early Warning Technology

Condition-based maintenance is to select the most suitable maintenance method according to the real-time operating state of the converter. Transformer condition evaluation and fault diagnosis is an important basis for condition maintenance, and it is also the key to ensure the normal implementation of condition maintenance. The main purpose of this paper is to study the application of voiceprint feature extraction in large-scale power transformers in uninterruptible power failure diagnosis and early warning technology. In this paper, a comprehensive and in-depth study of the state quantity of transformer uninterrupted detection is carried out. Experiments show that when CR<0.10, the matrix is satisfactory and consistent, and the weight distribution is reasonable.

Research on Extraction and Integration Method of Core Feature of Power Transformer under Incomplete Information

Background: The digital transformation strategy puts forward higher requirements for the information support system of the power system. Also, it points out the direction for the operation and maintenance of essential equipment such as large power transformers. However, the complex operating environment of power transformers poses a challenge to the digital operation and maintenance of equipment. Objective: Complex power transformer monitoring data is characterized by a wide range of sources, complex structures, incomplete information and unfocused distribution. This paper discussed and studied the Extraction and Integration Method of Core Feature of Power Transformer under Incomplete Information to fully exploit the potential value of power data and realize data collection and condition assessment of the equipment. Method: First, the power transformer holographic data perception technology and its analysis methods were explained from the perspective of multiple parameters; Then, based on actual cases, an information decision table based on incomplete information of power transformers based on equipment components and fault types was established to obtain the core feature of the power transformer itself; Secondly, by analyzing the distribution of the core feature index, a model for multi-task data integration and fusion in a cloud-edge-end architecture was proposed, and the integration method for multi-source data transfer was elaborated. Results: Finally, the feasibility of the proposed method was verified through simulation analysis of a calculation example. Conclusion: The method described in this article has a certain reference value for evaluating complex equipment that is mainly data-driven but lacks more serious information in the power grid digital transformation process.

Investigation on Vibration Characteristics of Amorphous Metal Alloy Core Dry-type Distribution Transformer

Large power transformers have severe vibration and noise problems. Thus, as the source of noise, it is vitally important to have accurate core vibration calculations. The calculation of the vibration is incredibly difficult to consider the complex propagation pathway of the vibration in the clamp and the Amorphous Metal Alloy Core Distribution Transformer (AMACDT). To understand the vibration characteristics of AMACDT, this manuscript provides a different approach on investigation of the vibration characteristics of an SCBH15-200/10 type. Based on the vibration characteristics calculation and displacement of an Amorphous Metal Alloy Core Distribution Transformer (AMACDT), they are obtained and solved using Finite Element Analysis software (FEA). Conferring to the outcomes of the vibration analysis, the method by adding bar-reinforcements on the upper clamp of transformer is proposed to lessen the vibration amplitude. To verify the usefulness and application of the suggested approach, the analytical results are obtained. The suggested approach is analyzed with those of experimental.

FEM-Based Power Transformer Model for Superconducting and Conventional Power Transformer Optimization

There were many promising superconducting materials discovered in the last decades that can significantly increase the efficiency of large power transformers. However, these large machines are generally custom-made and tailored to the given application. During the design process the most economical design should be selected from thousands of applicable solutions in a short design period. Due to the nonlinearity of the task, the cost-optimal transformer design, which has the smallest costs during the transformers’ planned lifetime, is usually not the design with the highest efficiency. Due to the topic’s importance, many simplified transformer models were published in the literature to resolve this problem. However, only a few papers considered this preliminary design optimization problem in the case of superconducting transformers and none of them made a comparison with a validated conventional transformer optimization model. This paper proposes a novel FEM-based two-winding transformer model, which can be used to calculate the main dimension of conventional and superconducting transformer designs. The models are stored in a unified JSON-file format, which can be easily integrated into an evolutionary or genetic algorithm-based optimization. The paper shows the used methods and their accuracy on conventional 10 MVA and superconducting 1.2 MVA transformer designs. Moreover, a simple cost optimization with the 10 MVA transformer was performed for two realistic economic scenarios. The results show that in some cases the cheaper, but less efficient, transformer can be the more economic.

Research of the Loss of Power Transformer Structure

This paper first introduces the research status of magnetic flux leakage and eddy current loss of power transformer at home and abroad, and discusses the significance and purpose of magnetic flux leakage and eddy current loss of power transformer metal components. At the same time, for the problems encountered in the calculation process of this paper, the corresponding solutions and the corresponding practical assumptions to simplify the calculation are given. In this paper, COMSOL software is used to establish the mathematical model of large power transformer and the actual three-dimensional finite element model of transformer, and the three-dimensional leakage magnetic field of large capa city transformer is accurately calculated. A surface impedance method based on double scalar magnetic potential is proposed. Using this method, the leakage magnetic field of structural parts of power transformer, such as pull plate, clamp, oil tank and so on, is analyzed and calculated The size and distribution of magnetic and eddy current losses. The simulation results are compared with the theoretical values to verify the validity and accuracy of the surface impedance method based on double scalar magnetic potential in analyzing the eddy current loss of large power transformer. Then this method is further applied to the analysis and calculation of magnetic leakage field and eddy current loss of a 6300kVA large power transformer to analyze the magnetic leakage field and eddy current loss of its metal components.

FINITE ELEMENT METHOD FOR NONLINEAR EDDY CURRENT PROBLEMS IN POWER TRANSFORMERS

An efficient finite element method to take account of the nonlinearity of the magnetic materials when analyzing three dimensional eddy current problems is presented in this paper. The problem is formulated in terms of vector and scalar potentials approximated by edge and node based finite element basis functions. The application of Galerkin techniques leads to a large, nonlinear system of ordinary differential equations in the time domain. The excitations are assumed to be time-periodic and the steady state periodic solution is of interest only. This is represented in the frequency domain as a Fourier series for each finite element degree of freedom and a finite number of harmonics is to be determined, i.e. a harmonic balance method is applied. Due to the nonlinearity, all harmonics are coupled to each other, so the size of the equation system is the number of harmonics times the number of degrees of freedom. The harmonics would be decoupled if the problem were linear, therefore, a special nonlinear iteration technique, the fixed-point method is used to linearize the equations by selecting a timeindependent permeability distribution, the so called fixed-point permeability in each nonlinear iteration step. This leads to uncoupled harmonics within these steps resulting in two advantages. One is that each harmonic is obtained by solving a system of algebraic equations with only as many unknowns as there are finite element degrees of freedom. A second benefit is that these systems are independent of each other and can be solved in parallel. The appropriate selection of the fixed point permeability accelerates the convergence of the nonlinear iteration. The method is applied to the analysis of a large power transformer. The solution of the electromagnetic field allows the computation of various losses like eddy current losses in the massive conducting parts (tank, clamping plates, tie bars, etc.) as well as the specific losses in the laminated parts (core, tank shielding, etc.). The effect of the presence of higher harmonics on these losses is investigated.

Determining Natural Resonant Frequencies of Large Power Transformer Windings

Design, assembly process and preparation of windings for large power transformers are complex procedures. It is very important to recognize resonant frequencies of the windings during the design phase in order to avoid increase of vibrations, stresses or noise levels during normal operation of the transformer. Increased vibrations and stresses can occur when the frequency of the excitation is close to the natural resonant frequency of the system. In that case amplitudes will increase, and their values will depend, among other factor, also on the amount of damping present in the system. Therefore, in order to avoid very large amplitude of vibration at resonance, the natural frequency must be known. In this work analytical calculation of natural frequencies of high voltage and low voltage windings, is described. Additionally, numerical analysis (FEA) is performed in the software package Ansys. Analysis contains descriptions of geometry simplifications, boundary conditions, mesh validation and applied loads. Finally, results obtained with numerical analysis (FEA) are compared with analytical results.

Magnetizing current of a Large Power Transformer and its Harmonic Spectrum in Normal and GIC conditions

A measurement of the harmonic spectrum of magnetizing current was performed. This paper analyzes the results of the measurement of harmonic spectrum of magnetizing current in standard noload test at various values of induction. Magnetizing current harmonic spectrum during single-phase noload test was measured as well as the impact of combined AC and DC magnetization on core behavior and harmonic spectrum. A mathematical model of transformer core is introduced. The calculated results are presented.

Large-Power Transformers: Time Now for Addressing Their Monitoring and Failure Investigation Techniques

Several review studies exist in the literature about monitoring, fault detection, and diagnosis of power transformers. However, they are general approaches in terms of power transformers. Some only focus on applying a specific class of techniques, but again, for general power transformers. Other reviews focus on applying different technologies such as fiber optics, thermal cameras, and vibration sensors, but all within the perspective of general power transformers. A significant question remains: among all types of power transformers, which specific techniques should be used, and why are they more adequate? What are the uncertainties that can decrease their precision? What about the balance, in terms of costs, associated with applying a certain technique and the return needed for a particular type of transformer? In this context, this paper is not only a literature review of well-known problems related to power transformers. Here, we do not just center on large power transformers (100 MVA or higher). Still, we describe a case study of a phase-shifting 1400 MVA-400 kV three-phase transformer that currently connects two European countries that began to show signs of abnormal operating conditions in 2012. In this way, the need to detect and identify anomalies in their initial stage of development for a possible preventive maintenance action is more than justified, which is essentially achieved with continuous monitoring models of the transformer, as concluded in this paper.